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  ## Details
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  - Model Name: Ethical Eye
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  - Hardware Requirements: The Ethical Eye model can be deployed on hardware configurations suitable for running deep learning models. Specific requirements may depend on the scale of deployment and the desired performance.
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  - Dependencies: The model relies on PyTorch, Transformers, and XLM-Roberta libraries. Refer to the model documentation for specific version requirements.
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  - Integration: Ethical Eye can be integrated into existing AI systems and platforms using the provided APIs and guidelines. Additional customization may be necessary to adapt the model to specific requirements.
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- - Ethical and Legal Considerations: While Ethical Eye aims to promote ethical behavior, it is important to acknowledge that it may have limitations and biases inherent in its training data. Developers should exercise caution and consider the legal and ethical implications of relying solely on the model's outputs without human oversight.
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-
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- ---
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- license: apache-2.0
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- ---
 
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+ ---
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+ license: apache-2.0
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+ requirements:
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+ - sentencepiece: >-
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+ (if not installed install using `pip install sentencepiece`, and restart
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+ runtime)
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+ library_name: transformers
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+ pipeline_tag: text-classification
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+ ---
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+
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  ## Details
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  - Model Name: Ethical Eye
 
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  - Hardware Requirements: The Ethical Eye model can be deployed on hardware configurations suitable for running deep learning models. Specific requirements may depend on the scale of deployment and the desired performance.
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  - Dependencies: The model relies on PyTorch, Transformers, and XLM-Roberta libraries. Refer to the model documentation for specific version requirements.
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  - Integration: Ethical Eye can be integrated into existing AI systems and platforms using the provided APIs and guidelines. Additional customization may be necessary to adapt the model to specific requirements.
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+ - Ethical and Legal Considerations: While Ethical Eye aims to promote ethical behavior, it is important to acknowledge that it may have limitations and biases inherent in its training data. Developers should exercise caution and consider the legal and ethical implications of relying solely on the model's outputs without human oversight.